RU2734493C1 - Method and apparatus for determining capacitance component parameters - Google Patents

Abstract

FIELD: physics.

SUBSTANCE: present invention relates to determination of capacity and loss factor of each of multiple capacitive components of power supply device. Disclosed method comprises steps of: a) obtaining for each capacitance component corresponding value of capacitance and value of loss factor, and b) processing values of capacity and value of loss factor, wherein treatment includes removal of total temperature effect on capacitance values from capacitance values and removal of total temperature effect on values of loss factor from values of loss factor to obtain for each capacitive component of temperature compensated value of capacitance and thermocompensated value of loss factor.

EFFECT: technical result is elimination of temperature effect on measurement results.

11 cl, 6 dwg

Description

TECHNICAL FIELD OF THE INVENTION

The present disclosure generally relates to the sizing of the capacitive component of a power supply device. In particular, it relates to a method for determining the capacitance and loss factor of a plurality of capacitive components of a power supply device.

LEVEL OF TECHNOLOGY

There is a need for bushing monitoring due to the fact that bushing failures account for about 10% of transformer failures. There are a number of different ways to determine the bushing parameters to assess the condition of the bushing. One technology is generally referred to as the total current method, in which the bushing bushing currents from all bushings of the transformer are measured and summed. As long as the vector sum is zero, it can generally be concluded that the bushings are functioning properly. If the vector sum is not zero, it can usually be concluded that there is a bushing fault. This method is generally independent of temperature because all capacitors of the bushing are equally susceptible to temperature changes. However, if, for example, the insulation of one of the bushings is damaged, the bushing may function differently due to local thermal conditions. US 6177803 discloses a summed current method and mentions the possibility of temperature compensation in this case. However, the summation current method is sensitive to system voltage fluctuations and will never provide any basic values for individual bushings such as capacitance and loss factor.

Another technique for detecting a bushing failure is based on comparing two bushings on the same phase. This method is called the “Reference Bushing Method”. Even if the reference bushing method is considered insensitive to system voltage fluctuations, it has been shown that the bushing parameters are influenced by the temperature difference between the two bushings forming part of the corresponding transformer due to different load, cooling conditions, service life, etc. ...

SUMMARY OF THE INVENTION

In light of the above, with respect to the reference bushing method, the present inventors have turned to the ability to estimate the capacitance and loss factor of multiple bushings of a single transformer based on the bushing tap current and the operating voltage at the top of the bushing, often referred to as "bushing absolute parameters." However, this method is unfortunately also sensitive to temperature changes.

In view of the above, an object of the present disclosure is to provide a method for determining the parameters of a capacitive component of a plurality of capacitive components of a power supply device that solves or at least mitigates the problems of the prior art.

Therefore, according to a first aspect of the present disclosure, there is provided a method for determining the capacitance and loss factor of each of a plurality of capacitive components of a power supply device, the method comprising the steps of: a) obtaining for each capacitive component a corresponding capacitance value and loss factor value, and b) processing the values capacitance and loss factor values, and the processing includes the steps at which the overall effect of temperature on the capacitance values is removed from the capacitance values and the overall temperature effect on the loss factor values is removed from the loss factor values to obtain a temperature-compensated capacitance value and a temperature-compensated value for each capacitive component loss factor.

The effect that can be obtained in this case is the ability to provide accurate on-line measurements of the capacitance and loss factor in the capacitive components of the electrical device. Loss factor is also commonly referred to as tan (δ) and is related to power factor. Power factor and loss factor are substantially equal for low loss factors, which is the case for capacitive applications, and therefore can be used interchangeably for this method.

The power supply device may, for example, be an electrical reactor device such as an electromagnetic induction device, for example a transformer such as a power transformer or a reactor, or a capacitive device such as a capacitor bank. The capacitive component or capacitive device may, for example, be capacitor bushing cores or capacitors of a capacitor bank.

In one embodiment, the overall effect of temperature on the capacitance values and loss factor values of the plurality of capacitive components is derived from a training period in which a plurality of capacitance values of each capacitive component and a plurality of loss factor values of each capacitive component were collected.

In one embodiment, the overall effect of temperature on capacity is derived from a statistical correlation analysis of a plurality of capacity values collected during the training period.

In one embodiment, the overall effect of temperature on the loss rate is obtained based on a statistical correlation analysis of a plurality of loss rate values obtained during the training period.

The learning period can, for example, be the measurements taken in the initial phase or the period when the capacitor determination device is put into operation.

The method can be based on gradual learning, and the learning period continues continuously, as well as during the execution of the method. Thus, the method can be used essentially immediately without any prior training period during commissioning. Thus, the accuracy of the method will gradually increase over time as more and more capacitance values of each capacitive component are collected and more and more values of the loss factor of each capacitive component are collected.

According to one embodiment, the processing includes the steps of transforming, by means of a first matrix of eigenvectors, a capacitance vector for which each element corresponds to one of the capacitance values, to obtain a transformed capacitance vector, and inversely transforming the transformed capacitance vector with the inverse of the corrected first eigenvector. vectors to obtain the corrected capacitance vector, which contains temperature-compensated capacitance values as its elements.

In one embodiment, the first eigenvector matrix contains the eigenvectors of the first covariance matrix of the training period capacitance matrix containing, for each capacitor, a plurality of capacitance values obtained during the training period.

The first covariance matrix can be normalized and scaled to determine the first eigenvector matrix.

In one embodiment, the corrected first eigenvector matrix has the elements of one of the eigenvectors set to zero.

According to one embodiment, the eigenvector whose elements are set to zero is the eigenvector that corresponds to the largest eigenvalue. The largest eigenvalue represents the largest overall change among capacity values. The largest overall change is the effect of temperature. By setting the corresponding eigenvector to zero in the corrected first eigenvector matrix, the overall temperature effect of the capacitance values is removed when the transformed capacitance vector is converted back using the inverse of the corrected first eigenvector matrix.

According to one embodiment, the processing includes the steps of transforming, by means of a second eigenvector matrix, a loss factor vector for which each element corresponds to one of the loss factor values to obtain a transformed loss factor vector, and converting the transformed loss factor vector with inversion the corrected second matrix of eigenvectors to obtain the corrected vector of the loss factor, which contains the temperature-compensated values of the loss factor as its elements.

According to one embodiment, the second eigenvector matrix contains the eigenvectors of the second covariance matrix of the training period loss factor matrix, containing for each bushing a plurality of loss factor values obtained during the training period.

The second covariance matrix can be normalized and scaled to determine the second eigenvector matrix.

In one embodiment, the corrected second eigenvector matrix has the elements of one of the eigenvectors set to zero.

According to one embodiment, the eigenvector whose elements are set to zero is the eigenvector that corresponds to the largest eigenvalue. The largest eigenvalue represents the largest overall change among loss factor values. The largest overall change is the effect of temperature. By setting the corresponding eigenvector to zero in the corrected first eigenvector matrix, the overall temperature effect of the loss factor values is removed when the transformed loss factor vector is converted back using the inverse of the corrected first eigenvector matrix.

One embodiment comprises providing an appropriate upper and lower threshold for each capacitance and each loss factor and generating an alarm if any of the temperature compensated capacitance values or temperature compensated loss factor values is outside the corresponding upper or lower threshold.

According to one embodiment, the acquisition includes the step of determining the corresponding capacitance value and the corresponding loss factor value based on the measurement of the corresponding bushing terminal voltage and the corresponding bushing tap current.

According to a second aspect of the present disclosure, there is provided a computer program comprising computer-executable components that, when triggered on a processing circuit of a capacitive component parameter determining apparatus, causes the capacitive component parameter determining apparatus to perform steps according to a method according to the first aspect.

According to a third aspect of the present disclosure, there is provided a computer program product comprising a storage medium including a computer program according to the second aspect.

According to a fourth aspect of the present disclosure, there is provided a capacitive component parameter determination apparatus configured to determine the capacitance and loss factor of each of a plurality of capacitive components of the power supply device, the capacitive component parameter determination apparatus comprising: a processing circuit and a storage medium containing computer-executable components that, when executed the processing circuit causes the capacitive component determination apparatus to execute the method steps according to the first aspect.

In general, all terms used in the claims are to be interpreted according to their usual meanings in the art, unless otherwise explicitly defined herein. All references to “element, device, component, facility, etc. singular "shall be interpreted openly as referring to at least one instance of an element, device, component, tool, etc., unless explicitly indicated otherwise.

BRIEF DESCRIPTION OF DRAWINGS

Specific embodiments of the inventive concept will now be described by way of example with reference to the accompanying drawings, in which:

FIG. 1 schematically shows an example of a device for determining the parameters of a capacitive component;

FIG. 2 shows a flowchart of a method performed by the capacitive component parameter determination apparatus of FIG. 1;

FIG. 3 shows a measurement setup for obtaining capacitance values and loss factor values of capacitive components of a power supply device;

FIG. 4a-4b schematically show plots of loss factor values and capacitance values, respectively, with and without temperature compensation, plotted over time; and

FIG. 5 schematically shows a graph of a bushing parameter, i.e. loss factor value or capacitance value, with upper and lower threshold values.

DETAILED DESCRIPTION

The inventive concept will now be described more fully with reference to the accompanying drawings, which show illustrative embodiments. The inventive concept can, however, be implemented in many different forms and should not be construed as limited to the options for implementation set forth in this document; rather, these embodiments are provided by way of example so that this disclosure is thorough and complete and will fully convey the scope of the inventive concept to those skilled in the art. Like items refer to like items throughout the description.

The present disclosure relates to a method for determining the capacitance and loss factor of a plurality of capacitances of a single power supply device. The method is particularly suitable for determining the parameters of a capacitive component of a power supply device comprising a plurality of capacitive components. In particular, the power supply is preferably a multi-phase power supply, that is, a power supply comprising a plurality of capacitive components, each capacitive component being associated with a corresponding electrical phase.

The method includes obtaining a capacitance value of each capacitive component and a loss factor value of each capacitive component. Therefore, a plurality of capacitance values and a plurality of loss factor values are obtained, with each capacitance value being associated with a corresponding one of the capacitive components, and each loss factor value being associated with a corresponding one of the capacitive components.

The capacitance values and loss factor values are processed to obtain for each capacitive component a temperature compensated capacitance value and a temperature compensated loss factor value. Processing includes removing the overall effect of temperature on capacitance values from capacitance values and removing the overall effect of temperature on loss factor values from loss factor values. In this way, temperature compensated capacitance values and temperature compensated loss factor values can be obtained.

Since all capacitive components are provided in the same power supply, there will be a general temperature effect on all capacitance values obtained and a general temperature effect on all obtained loss factor values. General influences on capacitance values are removed from capacitance values and general effects on loss factors are removed from loss factor values.

A capacitive component parameter determination apparatus configured to perform a method as disclosed herein will now be described with reference to FIG. 1. An exemplary device 1 for determining the parameters of a capacitive component comprises a processing circuit 3 and a data carrier 5. The storage medium 5 contains computer-executable components that, when triggered in the processing circuit 3, cause the capacitive component parameter determination apparatus 1 to execute a method as disclosed herein.

The processing circuit 3 uses any combination of one or more of a suitable central processing unit (CPU), multiprocessor, microcontroller, digital signal processor (DSP), application-specific integrated circuit (ASIC), programmable logic element array (FPGA), etc., capable of performing any of the operations disclosed herein relating to bushing dimensioning.

The storage medium 5 may, for example, be implemented as a memory such as random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM) or electrically erasable programmable read only memory (EEPROM) and, more specifically, as a non-volatile storage medium of a device in an external memory such as USB (Universal Serial Bus) or flash memory such as compact flash memory.

The capacitive component referred to herein may, for example, be a power supply bushing capacitor core or a capacitor bank capacitor.

FIG. 2 shows a method for determining the capacitance and loss factor of each of a plurality of capacitive components of a power supply device.

In step a), for each capacitive component of the electrical device, a corresponding capacitance value and a corresponding loss factor value are obtained by the processing circuit 3.

In the case of a bushing provided with a capacitor core, each capacitance value and loss factor value can, for example, be obtained from measurements of the corresponding bushing terminal voltage and the corresponding bushing tap current. Capacitance values and loss factor values can be estimated based on the corresponding bushing terminal voltage and bushing tap current.

FIG. 3 shows an example of a setup that measures the voltage V at the bushing terminal and the current I at the bushing terminal. For example, the voltage V at the bushing terminal can be obtained using a voltage transformer. The complex conductance Y of the bushing is equal to the current I of the bushing tap divided by the voltage at the terminal of the bushing, i.e. Y = I / V, and each capacitance value can be estimated by dividing the imaginary part of the complex conductance by the angular frequency of the system, i.e. C = Im (Y) / ω. The loss factor, or tan (δ), can be estimated by dividing the real part of the complex conductance with the complex part of the complex conductance, i.e. Re (Y) / Im (Y), which is equivalent to i _r / i _c , i.e. tan (δ) = i _r / i _c .

In step b), the capacitance values and the loss factor values are processed by the processing circuit 3. Processing involves removing the overall effect of temperature on capacitance values from capacitance values and removing the overall effect of temperature on loss factor values. Thus, for each capacitive component, a temperature-compensated capacitance value and a temperature-compensated loss factor value are obtained.

According to one example, the overall effect of temperature on capacitance values and the overall effect of temperature on loss factor values are derived from a plurality of capacitance values of each capacitive component and from a plurality of loss factor values of each capacitive component collected during a training period prior to starting the present method. In particular, statistical correlation analysis can be performed on this dataset, that is, on capacitance and loss factor values collected during the training period, whereby the overall effect of temperature on capacitance values and the overall effect of temperature on loss factor values can be determined. In this case, the general influences on temperature are usually given and thus ready for use in step b).

According to one example, this statistical correlation analysis may include the use of principal component analysis (PCA), as will be described in more detail below. It should be noted that other statistical correlation analysis methods can alternatively be used on a plurality of capacity values and loss rate values collected during the training period, for example, methods based on statistical regression.

In the case of PCA, the processing in step b) includes transforming, by the first matrix V _c, the eigenvectors of the capacity vector x _c , for which each element corresponds to one of the capacitance values obtained in step a), to obtain a transformed capacity vector y _c . Consequently, a transformation of the type V _c * x _c = y _{c is} performed, where the columns of the first matrix V _{c of} eigenvectors are the eigenvectors of the first covariance matrix X _{cco of the} capacitive matrix X _c of the training period, obtained during the training period. In particular, the matrix X _{c of the} capacity of the training period contains a set of values of the capacity of each capacitive component obtained during the training period. As an example, the first eigenvector matrix can be a 3 * 3 V _c = [V _1c V _2c V _3c ] matrix in the case where the electromagnetic induction device has three electrical phases and therefore three capacitive components, with V _1c -V _3c are eigenvectors arranged in the form of columns, x = (c ₁ , c ₂ , c ₃ ) is a vector containing three components c ₁ -c ₃ , which represent the three capacitance values obtained in step a).

The transformed capacitance vector y _{c is} then converted back by means of an inverted corrected first eigenvector matrix V _c 'to obtain a corrected capacitance vector x _c ' which contains temperature compensated capacitance values as its elements. For this, the transformation (V _c ') ^-1 y _c = x _c ' is performed, where x _c '= (c ₁ ', c ₂ ', c ₃ ') contains temperature-compensated capacitance values.

The corrected first eigenvector matrix V _c 'has the elements of one of the eigenvectors set to zero. In particular, the eigenvector, whose elements are set to zero, is the eigenvector that corresponds to the largest eigenvalue or singular value, therefore, in the general case of an n-capacitive component, the corrected first matrix of eigenvectors has the form V _c '= (0 V _c2 ... V _cn ), and in the example with three capacitive components, the corrected first eigenvector matrix is V _c '= (0 V _c2 V _c3 ).

Since the capacity matrix X _c , as a rule, is an m * n matrix, where m ≠ n, diagonalization of its covariance matrix, that is, the first covariance matrix X _cco , is impossible, and for this purpose, other methods can be used to obtain “eigenvalues” factorization of the first covariance matrix X _cco . Singular value decomposition (SVD) can, for example, be used to obtain the first eigenvector matrix V _c .

As noted above, the matrix X _c capacitance training period to capacitances comprises a plurality of capacitance values of each capacitance component is collected during the training period, and in the case of a three-phase system the capacitive component matrix may be in the form _{X c = (X c1 X c2} X c3) and more generally, X _c = (X _c1 ... X _cn ), where X _ck is a vector of columns with m elements, each of which is the value of the capacity of the k-th capacitive component obtained during the training period.

It can also be noted that the training period capacity matrix X _c can be normalized and scaled before the first covariance matrix X _{cco is determined} . Normalization can involve taking the average of each column and subtracting the average of the column from the items in the column. Scaling can, for example, involve dividing items in each column with the standard deviation of items in the column.

The processing in step b) further includes transforming, by means of the second eigenvector matrix V _{tan (δ),} the loss factor vector x _{tan (δ)} , for which each element corresponds to one of the loss factor values obtained in step a), to obtain a transformed vector of the loss factor y _{tan (δ)} . Therefore, a transformation of the type V _{tan (δ)} * x _{tan (δ)} = y _{tan (δ) is} performed, where the columns of the second eigenvector matrix V _{tan (δ)} are the eigenvectors of the second covariance matrix X _{tan (δ) co of} the period loss coefficient matrix training X _{tan (δ)} obtained during the training period. In particular, the training period loss factor matrix X _{tan (δ)} contains a plurality of loss factor values of each capacitive component obtained during the learning period. As an example, the second matrix of eigenvectors can be the matrix V _{tan (δ)} = [V _{1tan (δ)} V _{2tan (δ)} V _{3tan (δ)} ] in the case where the electromagnetic induction device has three electrical phases and therefore three capacitive components, and V _{1tan (δ)} -V _{3tan (δ)} are eigenvectors arranged in the form of columns, and x _{tan (δ)} = (tan (δ) ₁ , tan (δ) ₂ , tan (δ) ₃ ) is a vector containing three components c ₁ -c ₃ , which represent three values of the loss factor obtained in step a).

The transformed loss factor vector y _{tan (δ) is} then converted back by inversely inverting the corrected second eigenvector matrix V _{tan (δ)} 'to obtain a corrected loss factor vector x _{tan (δ)} ' which contains the temperature compensated loss factor values as its elements. To do this, perform the transformation (V _{tan (δ)} ') ^-1 y _{tan (δ)} = x _{tan (δ)} ', where x _{tan (δ)} '= (tan (δ) ₁ ', tan (δ) ₂ ', tan (δ) ₃ ') contains the temperature compensated loss factor values.

The corrected second eigenvector matrix V _{tan (δ)} 'has the elements of one of the eigenvectors set to zero. In particular, the eigenvector, whose elements are set to zero, is the eigenvector that corresponds to the largest eigenvalue or singular value, therefore, in the general case of an n-capacitive component, the corrected second eigenvector matrix has the form V _{tan (δ)} '= (0 V _{tan (δ) 2} ... V _{tan (δ) n} ), and in the example with three capacitive components V _{tan (δ)} '= (0 V _{tan (δ) 2} V _{tan (δ) 3} ).

Since the matrix X _{tan (δ) of} the training period loss coefficient is usually an m * n matrix, where m ≠ n, diagonalization of its covariance matrix, that is, the second covariance matrix X _{tan (δ) co} , is impossible, and for this purpose to obtain "eigenvalues" can use other methods of factorization of the second covariance matrix X _{tan (δ) co} . Singular value decomposition (SVD) can, for example, be used to obtain a second matrix V _{tan (δ) of} eigenvectors.

As noted earlier, the learning period loss factor matrix X _{tan (δ)} for loss factor values may contain a plurality of loss factor values of each capacitive component collected during the learning period, and in the case of a three-phase system, the learning period loss factor matrix may be of the form X _{tan ( δ)} = (Xtan (δ) ₁ Xtan (δ) ₂ Xtan (δ) ₃ ), and more generally X _{tan (δ)} = (Xtan (δ) ₁ ... Xtan (δ) _n ), where Xtan (δ ) _k is a vector of columns with m elements, each of which is the value of the loss factor of the k-th capacitive component obtained during the training period.

It can also be noted that the training period loss factor matrix X _{tan (δ)} may be normalized and scaled before the second covariance matrix X _{tan (δ) co is} determined. Normalization can involve taking the average of each column and subtracting the average of the column from the items in the column. Scaling can, for example, involve dividing items in each column with the standard deviation of items in the column.

Figures 4a and 4b show examples of temperature compensated loss factor values in comparison with uncompensated initially obtained loss factor values, i.e. values obtained in step a), but without processing in step b), and temperature-compensated capacitance values compared to uncompensated capacitance values in the context of bushings.

FIG. 4a, the loss factor values are plotted for each of the three bushings of the electromagnetic induction device. Curves 7a, 9a and 11a show the temperature compensated loss factor of the three bushings over time, while curves 7b, 9b and 11b show the corresponding uncompensated loss factor values. As can be seen, the temperature compensated loss factor curves 7a-11a are much less subject to fluctuations and provide a good measure of the actual absolute loss factor values of the bushings. Similarly, in FIG. 4b, the capacitance values are plotted for each of the three power supply bushings. Curves 13a, 15a and 17a show the temperature compensated capacitance values of the three bushings over time, while curves 13b-17b show the corresponding temperature compensated capacitance values.

Since the temperature compensated loss factor and capacitance values provide accurate estimates of the loss factor and capacitance of the bushings, these values can be used to determine if there is a capacitance failure or a power supply failure. Thus, according to one example, corresponding upper threshold U and lower threshold L can be provided for each capacitance and each loss factor, as shown in FIG. 5 for only one capacity parameter, i.e. graph 19, which shows one of the two parameters of the capacitive component discussed here. The upper and lower thresholds U and L provide a range for each capacitive component and for each parameter of the capacitive component within which the capacitance or loss factor is allowed to vary. In the event that any of the temperature compensated capacitance values or the temperature compensated loss factor values exceed the corresponding upper or lower threshold value, an alarm can be generated to thereby alert the operator to the presence of a malfunction.

The inventive concept has mainly been described above with reference to a few examples. However, as one skilled in the art will appreciate, other embodiments than those disclosed above are equally possible within the scope of the inventive concept as defined by the appended claims.

Claims (19)

1. A method for determining the capacitance and loss factor of each of the plurality of capacitive components of a power supply device, said method comprising the steps of: measure the voltage and current of each capacitive component, calculating the complex conductance for each capacitive component using the corresponding voltage and corresponding current, obtaining for each capacitive component the corresponding capacitance value and loss factor value using the corresponding complex conductance, and process capacitance values and loss factor values, said processing including the steps of removing the overall effect of temperature on the capacitance values from the capacitance values and removing the overall temperature effect on the loss factor values from the loss factor values to obtain a temperature-compensated value for each capacitive component capacitance and temperature-compensated loss factor, wherein said processing includes the steps of transforming, by means of the first matrix of eigenvectors, the capacitance vector, for which each element corresponds to one of the capacitance values, to obtain the transformed capacitance vector, and converting the transformed capacitance vector with inversion of the corrected first matrix of eigenvectors to obtain of the corrected capacitance vector, which contains temperature-compensated capacitance values as its elements, and the corrected first matrix of eigenvectors has the elements of one of the eigenvectors set to zero, and the eigenvector, which has its elements set to zero, is the eigenvector that corresponds to the greatest eigenvalue, wherein the first eigenvector matrix contains the eigenvectors of the first covariance matrix of the training period capacity matrix, containing for each capacitive component a set of capacity values obtained during the training period. 2. The method of claim 1, wherein the overall effect of temperature on capacitance values and loss factor values of the plurality of bushings is obtained based on a training period in which a plurality of capacitance values of each capacitive component and a plurality of loss factor values of each capacitive component were collected. 3. The method of claim 2, wherein the overall effect of temperature on the capacitance is obtained based on a statistical correlation analysis of a plurality of capacitance values collected during the training period. 4. The method according to claim 2 or 3, in which the overall effect of temperature on the loss factor is obtained on the basis of a statistical correlation analysis of the set of loss factor values obtained during the training period. 5. The method according to any one of the preceding claims, wherein said processing includes transforming, by means of a second eigenvector matrix, a loss factor vector for which each element is corresponding to one of the loss factor values to obtain a transformed loss factor vector, and converting the transformed vector of the vector of the loss factor with inversion of the corrected second matrix of eigenvectors to obtain the corrected vector of the loss factor, which contains temperature compensated values of the loss factor as its elements. 6. The method according to claim 5, wherein the second eigenvector matrix contains the eigenvectors of the second covariance matrix of the training period loss factor matrix containing for each capacitive component a plurality of loss factor values obtained during the training period. 7. The method of claim 5 or 6, wherein the corrected second eigenvector matrix has the elements of one of the eigenvectors set to zero. 8. The method of claim 7, wherein the eigenvector that has its elements set to zero is the eigenvector that corresponds to the largest eigenvalue. 9. The method according to any of the preceding claims, comprising the steps of providing corresponding upper and lower threshold values for each capacitance and each loss factor, and generating an alarm if any of the temperature compensated capacitance values or temperature compensated loss factor values is out of range said corresponding upper or lower threshold. 10. A storage medium containing a computer program stored thereon and containing computer-executable components, which, when triggered in the processing circuit of the capacitive component parameter determining device, causes the capacitive component parameter determining device (1) to carry out the steps according to the method according to any one of claims. 1-9. 11. Device (1) for determining the parameters of the capacitive component, configured to determine the capacitance and loss factor of each of the plurality of capacitive components of the power supply device, and the device for determining the parameters of the capacitive component comprises: processing scheme (3), and a data carrier (5) containing computer-executable components, which, when executed by the processing circuit (5), cause the device (1) for determining the parameters of the capacitive component to perform the method steps according to any one of claims. 1-9.

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